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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

The 1983 direct strike lightning data, part 3

Data waveforms are presented which were obtained during the 1983 direct strike lightning tests utilizing the NASA F106-B aircraft specially instrumented for lightning electromagnetic measurements. The aircraft was operated in the vicinity of the NASA Langley Research Center, Hampton, Virginia, in a thunderstorm environment to elicit strikes. Electromagnetic field data and conduction currents on the aircraft were recorded for attached lightning. Part 3 contains 446 pages of charts depicting additional lightning strike data.

Thomas, Mitchel E.↗
DOE OSTI2024

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗
NASA NTRS1980

An airborne short wave infrared /SWIR/ pushbroom imaging system using a 64-element PbS detector array

Research evidence indicates that data in the short wave infrared (SWIR) spectral region will greatly improve the information content of remotely sensed data. Bands are required in the 1.55-1.75 micron and 2.08-2.35 micron spectral regions for a variety of agricultural and geological investigations. It is anticipated that future Landsat sensors will use pushbroom linear array technology to obtain high resolution, improved sensitivity and increased system reliability. To obtain early laboratory and field data, an airborne pushbroom image system has been designed for operation in the short wave infrared spectral region. The system uses a 64-element staggered PbS array and is operated at 195 K; the instrument has been designed to operate in an aircraft and will view a 19 degree swath width with a 5.8 mrad IFOV. The spectral bandwidth of each channel is .05 micron and the noise equivalent reflectivity in the order of .2% is provided. The requirements for more advanced detector arrays for use in future NASA spacecraft remote sensing instruments are also discussed.

Husain-Abidi, A. S.↗
NASA NTRS1986

The 1984 direct strike lightning data, part 1

Data waveforms are presented which were obtained during the 1984 direct-strike lightning tests utilizing the NASA F106-B aircraft specially instrumented for lightning electromagnetic measurements. The aircraft was operated in the vicinity of the NASA Langley Research Center, Hampton, Virginia, in a thunderstorm environment to elicit strikes. Electromagnetic field data and conduction currents on the aircraft were recorded for attached lightning. The entire transient recorder data obtained for 247 uses and 11 nearby flashes in the 1984 campaign are presented. This is part 1, consisting of summary and conclusion.

Thomas, Mitchel E.↗
NASA NTRS1986

The 1984 direct strike lightning data, part 2

Data waveforms are presented which were obtained during the 1984 direct-strike lightning tests utilizing the NASA F106-B aircraft specially instrumented for lightning electromagnetic measurements. The aircraft was operated in the vicinity of the NASA Langley Research Center, Hampton, Virginia, in a thunderstorm environment to elicit strikes. Electromagnetic field data and conduction currents on the aircraft were recorded for attached lightning. This is part 2, consisting entirely of charts and graphs.

Thomas, Mitchel E.↗
NASA NTRS1986

The 1984 direct strike lightning data, part 3

Data waveforms are presented which were obtained during the 1984 direct-strike lightning tests utilizing the NASA F106-B aircraft specially instrumented for lightning electromagnetic measurements. The aircraft was operated in the vicinity of the NASA Langley Research Center, Hampton, Virginia, in a thunderstorm environment to elicit strikes. Electromagnetic field data and conduction currents on the aircraft were recorded for attached lightning. This is part 3, consisting entirely of charts and graphs.

Thomas, Mitchel E.↗
DOE OSTI2020

UNESE Data Analysis - Disko Elm Gas Transport Characteristics (NA-22 Quarterly Report)

Two research papers describing gas transport studies in subsurface containment environments appropriate for underground nuclear explosions were revised and accepted for publication in the peer-reviewed journals, Nature – Scientific Reports and Journal of Geophysical Research. The Nature – Scientific Reports paper is a primary deliverable and describes the gas-transport experiment performed in P Tunnel (NNSS) and 1) subsequent analysis of field data as part of the UNESE program. The Journal of Geophysical Research paper describes an experiment, supported mainly by DARPA and led by researchers at Weston Geophysical and New Mexico Tech., with 2) analyses supported by this project to evaluate the ability of SF6 gas tracer to track xenon gas migration under conditions related to a previous UNESE experiment. Two new tasks consider 3) evaluation of detonation heating and multiphase flow on arrival of xenon at the surface and 4) the impact of surface or Langmuir adsorption of gases being transported through pores and along fractures.

58 GEOSCIENCES↗
DOE OSTI2024

Semi–Analytical Modeling of Transient Stream Drawdown and Depletion in Response to Aquifer Pumping

Analytical and semi–analytical models for stream depletion with transient stream stage drawdown induced by groundwater pumping are developed to address a deficiency in existing models, namely, the use of a fixed stream stage condition at the stream–aquifer interface. Here field data are presented to demonstrate that stream stage drawdown does indeed occur in response to groundwater pumping near aquifer–connected streams. A model that predicts stream depletion with transient stream drawdown is developed based on stream channel mass conservation and finite stream channel storage. The resulting models are shown to reduce to existing fixed–stage models in the limit as stream channel storage becomes infinitely large, and to the confined aquifer flow with a no–flow boundary at the streambed in the limit as stream storage becomes vanishingly small. The model is applied to field measurements of aquifer and stream drawdown, giving estimates of aquifer hydraulic parameters, streambed conductance, and a measure of stream channel storage. The results of the modeling and data analysis presented herein have implications for sustainable groundwater management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

On the configuration of the magnetotail near midnight during quiet and weakly disturbed periods - State of the magnetosphere

Particle and field data are analyzed for a number of magnetically quiet days. It is shown that the magnetotail near midnight may exist for hours at a time in widely different quasi-stable configurations which, in their limit, can be characterized as being (1) fairly dipolelike to about 15 R(E), beyond which the field becomes taillike; and (2) dipolelike to only about 10 R(E), beyond which the field becomes taillike. These different states affect both the dynamics of the substorm and the evolution of the pitch angle distributions of energetic electrons in the near-earth plasma sheet past midnight. During quiet times, the plasma sheet in its azimuthal variation is at its thinnest in the region near midnight.

West, H. I., Jr.↗
NASA NTRS2004

Potential of Radar Imaging and Sounding Methods in Mapping Heavily Eroded Impact Craters: Mapping Some Structural Elements of the Hico Crater, TX

Shuttle Radar Topography Mission (SRTM) and Ground Penetrating Radar (GPR) data collected over an area north of the town of Hico, central Texas, have been used to map disturbances in the surface topography and subsurface stratigraphy. The Radar topography results confirm the presence of multiple rings suggestive of an impact crater. Correlation between the orbital SRTM and on-the-ground GPR field data are affected by different biases related to variations in terrain and vegetation cover. Nevertheless, the correspondence of the two data sets supports the earlier conclusions that a complex, multiple ring impact structure is reflected in the topography of this area. The SRTM data reveal three previously unrecognized rings; with the outermost ring some 5-6 km in diameter. The crater appears to be significantly larger than the size (2.5 km diameter) previously inferred on the basis of aerial images. In addition, the GPR data suggest the presence of subsurface faulting that spatially coincides with the two inner rings of the crater. This suggests that the topographic rings are structurally controlled by faulting.

Heggy, E.↗
NASA NTRS2003

Algorithms for Processing and Analysis of Ocean Color Satellite Data for Coastal Case 2 Waters

SeaWiFS has the ability to enhance our understanding of many oceanographic processes. However, its utility in the coastal zone has been limited by valid bio-optical algorithms and by the determination of accurate water reflectances, particularly in the blue bands (412-490 nm), which have a significant impact on the effectiveness of all bio-optical algorithms. We have made advances in three areas: algorithm development (Table 16.1), field data collection, and data applications.

Stumpf, Richard P.↗
DOE OSTI2023

CreelCat, a Catalog of United States Inland Creel and Angler Survey Data

The United States Inland Creel and Angler Survey Catalog (CreelCat) contains a national compilation of angler and creel survey data collected by natural resource management agencies across the United States (including Washington, D.C. and Puerto Rico). These surveys are used to help inform the management of recreational fisheries, by collecting information about anglers including what they are catching and harvesting, the amount of effort they expend, their angling preferences, and demographic information. As of May 1, 2023, CreelCat houses over 14,729 surveys from 33 states, Puerto Rico, and Washington, D.C., comprising 235 data fields across 8 tables. These tables contain 235,015 records of fish catch and harvest metrics, 27,250 angler preference metrics, 14,729 records of survey characteristics, 13,576 records of effort metrics, and 409 records of angler demographics. Though individual creel surveys are often deployed to meet local science and management objectives, creel data aggregated across jurisdictions has the potential to address larger scale research and management needs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network - that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest-in the sense of electrical distance - from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for realtime operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

distribution service transformer↗
NASA NTRS1975

Modelling the magnetosphere of Mercury

A model magnetosphere for Mercury is presented using an upstream image-dipole and nightside 2-dimensional tail current sheet method. The tail field is represented by an analytical formulation. Magnetic field data from the Mercury 1 encounter by Mariner 10 in March 1974 are used to determine quantitative parameters of the model magnetosphere, using the method of least squares. The magnetopause crossing points directly observed are used to determine the size of the magnetosphere, and the solar wind conditions are used to determine the magnetospheric field at the stagnation point. The model produces a magnetosphere-like region with planetary field lines that are confined in nearly circular cross-sections transverse to the sun-planet line. Results are used to show geometry, field line configuration, and contours of constant field intensity inside the magnetosphere.

Whang, Y. C.↗
NASA NTRS1989

A test of magnetic field draping induced Bz perturbations ahead of fast coronal mass ejecta

ICE plasma and magnetic field data are examined to look for observational evidence of IMF draping ahead of fast coronal mass ejections (CMEs). The utility of the draping model for predicting the Bz perturbations and hence geomagnetic activity associated with the sheath regions ahead of such CMEs is also examined. A simple prediction scheme based on the upstream radial field component is developed and a set of interplanetary shock events previously associated with interplanetary type II bursts, and hence solar source locations, is used. Of 17 events the radial component predictor developed here correctly predicts the direction considered of the Bz perturbations for 13 events (76 percent). While this result is certainly not conclusive, it is considered to be supportive of the draping scenario.

Mccomas, D. J.↗
DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Data-driven Whitney forms for structure-preserving control volume analysis

Control volume analysis models physics via the exchange of generalized fluxes between subdomains. Here, we introduce a scientific machine learning framework adopting a partition of unity architecture to identify physically-relevant control volumes, with generalized fluxes between subdomains encoded via Whitney forms. The approach provides a differentiable parameterization of geometry which may be trained in an end-to-end fashion to extract reduced models from full field data while exactly preserving physics. The architecture admits a data-driven finite element exterior calculus allowing discovery of mixed finite element spaces with closed form quadrature rules. An equivalence between Whitney forms and graph networks reveals that the geometric problem of control volume learning is equivalent to an unsupervised graph discovery problem. The framework is developed for manifolds in arbitrary dimension, with examples provided for H(div) problems in $\mathbb{R}$ establishing convergence and structure preservation properties. Finally, we consider a lithium-ion battery problem where we discover a reduced finite element space encoding transport pathways from high-fidelity microstructure resolved simulations. The approach reduces the 5.89M finite element simulation to 136 elements while reproducing pressure to under 0.1% error and preserving conservation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Abstract Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

25 ENERGY STORAGE↗